[Skip to Content]

Claim CME

Public Health

Variation in US Hospital Mortality Rates for Patients Admitted With COVID-19 During the First 6 Months of the Pandemic

Educational Objective
To identify the key insights or developments described in this article

1 Credit CME

JAMA Internal Medicine

Published Online: December 22, 2020

Original Investigation

Article Information and Disclosures

David A. Asch, MD, MBA^1,2;

Natalie E. Sheils, PhD³;

Md Nazmul Islam, PhD, MBA³;

Yong Chen, PhD⁴;

Rachel M. Werner, MD, PhD^1,2,5;

John Buresh, BS³;

Jalpa A. Doshi, PhD^1,2

Author Affiliations

¹Division of General Internal Medicine, University of Pennsylvania, Philadelphia
²Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
³UnitedHealth Group, Minnetonka, Minnesota
⁴Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia
⁵Cpl Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania

Read article on JAMA Network

Read Article Claim CME

Key Points

Question Are hospital outcomes for patients with coronavirus disease 2019 (COVID-19) improving?

Findings In this cohort study of 38 517 adults who were admitted with COVID-19 to 955 US hospitals, rates of 30-day mortality or referral to hospice varied from 9.06% to 15.65% in the best- and worst-performing quintiles. In the early months of the pandemic, 94% of hospitals in a subset of 398 improved by at least 25%, and the strongest determinant of improvements in hospital-level outcome was a decline in community rates of infection.

Meaning All else being equal, COVID-19 mortality in hospitals seems to be lower when the prevalence of COVID-19 in their surrounding communities is lower.

Abstract

Importance It is unknown how much the mortality of patients with coronavirus disease 2019 (COVID-19) depends on the hospital that cares for them, and whether COVID-19 hospital mortality rates are improving.

Objective To identify variation in COVID-19 mortality rates and how those rates have changed over the first months of the pandemic.

Design, Setting, and Participants This cohort study assessed 38 517 adults who were admitted with COVID-19 to 955 US hospitals from January 1, 2020, to June 30, 2020, and a subset of 27 801 adults (72.2%) who were admitted to 398 of these hospitals that treated at least 10 patients with COVID-19 during 2 periods (January 1 to April 30, 2020, and May 1 to June 30, 2020).

Exposures Hospital characteristics, including size, the number of intensive care unit beds, academic and profit status, hospital setting, and regional characteristics, including COVID-19 case burden.

Main Outcomes and Measures The primary outcome was the hospital’s risk-standardized event rate (RSER) of 30-day in-hospital mortality or referral to hospice adjusted for patient-level characteristics, including demographic data, comorbidities, community or nursing facility admission source, and time since January 1, 2020. We examined whether hospital characteristics were associated with RSERs or their change over time.

Results The mean (SD) age among participants (18 888 men [49.0%]) was 70.2 (15.5) years. The mean (SD) hospital-level RSER for the 955 hospitals was 11.8% (2.5%). The mean RSER in the worst-performing quintile of hospitals was 15.65% compared with 9.06% in the best-performing quintile (absolute difference, 6.59 percentage points; 95% CI, 6.38%-6.80%; P < .001). Mean RSERs in all but 1 of the 398 hospitals improved; 376 (94%) improved by at least 25%. The overall mean (SD) RSER declined from 16.6% (4.0%) to 9.3% (2.1%). The absolute difference in rates of mortality or referral to hospice between the worst- and best-performing quintiles of hospitals decreased from 10.54 percentage points (95% CI, 10.03%-11.05%; P < .001) to 5.59 percentage points (95% CI, 5.33%-5.86%; P < .001). Higher county-level COVID-19 case rates were associated with worse RSERs, and case rate declines were associated with improvement in RSERs.

Conclusions and Relevance Over the first months of the pandemic, COVID-19 mortality rates in this cohort of US hospitals declined. Hospitals did better when the prevalence of COVID-19 in their surrounding communities was lower.

Claim CME

Sign in to take quiz and track your certificates

Buy This Activity

Article Information

Accepted for Publication: November 14, 2020.

Published Online: December 22, 2020. doi:10.1001/jamainternmed.2020.8193

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2020 Asch DA et al. JAMA Internal Medicine.

Corresponding Author: David A. Asch, MD, Center for Health Care Innovation, 3400 Civic Center Blvd, PCAM South Tower 14-171, Philadelphia, PA 19104 (asch@wharton.upenn.edu).

Author Contributions: Dr Islam and Mr Buresh had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: All authors.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: All authors.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Sheils, Islam, Werner, Buresh, Chen.

Supervision: Sheils, Werner, Doshi.

Conflict of Interest Disclosures: Dr Doshi reported personal fees from AbbVie, Boehringer Ingelheim, Janssen, Kite Pharma, and Merck and grants from AbbVie, Janssen, Novartis, Merck, Pfizer, PhRMA, Regeneron, and Sanofi and outside the submitted work. No other disclosures were reported.

References

American Hospital Association. AHA annual survey database. Accessed July 29, 2020. https://www.ahadata.com/aha-annual-survey-database

US Centers for Medicare & Medicaid Services. FY 2020 final rule and correction notice data files. Accessed June 29, 2020. https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/FY2020-IPPS-Final-Rule-Home-Page-Items/FY2020-IPPS-Final-Rule-Data-Files

US Centers for Medicare & Medicaid Services. 2019 POS file. Accessed September 4, 2020. https://www.cms.gov/research-statistics-data-systems/provider-services-current-files/2019-pos-file

New York Times. Date, county, state, fips, cases, deaths. Accessed November 1, 2020. https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-counties.csv

National Quality Forum. Measure evaluation criteria and guidance for evaluating measures for endorsement. Accessed September 1, 2019. http://www.qualityforum.org/docs/measure_evaluation_criterias.aspx

George EI , Ročková V , Rosenbaum PR , Satopää VA , Silber JH . Mortality rate estimation and standardization for public reporting: Medicare’s Hospital Compare. J Am Stat Assoc. 2017;112:519, 933-947. doi:10.1080/01621459.2016.1276021 Google Scholar Crossref

Silber JH , Rosenbaum PR , Brachet TJ , et al. The Hospital Compare mortality model and the volume-outcome relationship. Health Serv Res. 2010;45(5 Pt 1):1148-1167. doi:10.1111/j.1475-6773.2010.01130.x PubMed Google Scholar Crossref

Silber JH , Satopää VA , Mukherjee N , et al. Improving Medicare’s Hospital Compare Mortality Model. Health Serv Res. 2016;51(suppl 2):1229-1247. doi:10.1111/1475-6773.12478 PubMed Google Scholar Crossref

Silber JH , Rosenbaum PR , Niknam BA , et al. Comparing outcomes and costs of surgical patients treated at major teaching and nonteaching hospitals: a national matched analysis. Ann Surg. 2020;271(3):412-421. doi:10.1097/SLA.0000000000003602 PubMed Google Scholar Crossref

Elixhauser A , Steiner C , Harris DR , Coffey RM . Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8-27. doi:10.1097/00005650-199801000-00004 PubMed Google Scholar Crossref

Drye EE , Normand SL , Wang Y , et al. Comparison of hospital risk-standardized mortality rates calculated by using in-hospital and 30-day models: an observational study with implications for hospital profiling. Ann Intern Med. 2012;156(1 Pt 1):19-26. doi:10.7326/0003-4819-156-1-201201030-00004 PubMed Google Scholar Crossref

Normand S-LT , Shahian DM . Statistical and clinical aspects of hospital outcomes profiling. Stat Sci. 2007;22:206-226. doi:10.1214/088342307000000096 Google Scholar Crossref

Bland JM , Altman DG . Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;1(8476):307-310. doi:10.1016/S0140-6736(86)90837-8 PubMed Google Scholar Crossref

R Core Team. R: a language and environment for statistical computing. Accessed December 12, 2020. http://www.R-project.org/.

Gupta S , Hayek SS , Wang W , et al; STOP-COVID Investigators. Factors associated with death in critically ill patients with coronavirus disease 2019 in the US. JAMA Intern Med. 2020. doi:10.1001/jamainternmed.2020.3596 PubMed Google Scholar

Horwitz LI , Jones SA , Cerfolio RJ , et al. Trends in COVID-19 risk-adjusted mortality rates. J Hosp Med. 2020. Published online October 23, 2020. doi:10.12788/jhm.3552 PubMed Google Scholar

US Food and Drug Administration. Veklury (remdesivir) EUA letter of approval. Accessed December 12, 2020. https://www.fda.gov/media/137564/download

Spinner CD , Gottlieb RL , Criner GJ , et al; GS-US-540-5774 Investigators. Effect of remdesivir vs standard care on clinical status at 11 days in patients with moderate COVID-19: a randomized clinical trial. JAMA. 2020;324(11):1048-1057. doi:10.1001/jama.2020.16349 PubMed Google Scholar Crossref

https://www.ox.ac.uk/news/2020-06-16-low-cost-dexamethasone-reduces-death-one-third-hospitalised-patients-severe

Horby P , Lim WS , Emberson JR , et al; RECOVERY Collaborative Group. Dexamethasone in hospitalized patients with covid-19—preliminary report. N Engl J Med. 2020. doi:10.1101/2020.06.22.20137273 PubMed Google Scholar

Gandhi M , Rutherford GW . Facial masking for covid-19—potential for “variolation” as we await a vaccine. N Engl J Med. 2020;383(18):e101. doi:10.1056/NEJMp2026913 PubMed Google Scholar

Chassin MR , Park RE , Lohr KN , Keesey J , Brook RH . Differences among hospitals in Medicare patient mortality. Health Serv Res. 1989;24(1):1-31.PubMed Google Scholar

Jha AK , Li Z , Orav EJ , Epstein AM . Care in US hospitals —the Hospital Quality Alliance program. N Engl J Med. 2005;353(3):265-274. doi:10.1056/NEJMsa051249 PubMed Google Scholar Crossref

Tsai TC , Joynt KE , Orav EJ , Gawande AA , Jha AK . Variation in surgical-readmission rates and quality of hospital care. N Engl J Med. 2013;369(12):1134-1142. doi:10.1056/NEJMsa1303118 PubMed Google Scholar Crossref

AMA CME Accreditation Information

Credit Designation Statement: The American Medical Association designates this Journal-based CME activity activity for a maximum of 1.00  AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Successful completion of this CME activity, which includes participation in the evaluation component, enables the participant to earn up to:

1.00 Medical Knowledge MOC points in the American Board of Internal Medicine's (ABIM) Maintenance of Certification (MOC) program;;
1.00 Self-Assessment points in the American Board of Otolaryngology – Head and Neck Surgery’s (ABOHNS) Continuing Certification program;
1.00 MOC points in the American Board of Pediatrics’ (ABP) Maintenance of Certification (MOC) program;
1.00 Lifelong Learning points in the American Board of Pathology’s (ABPath) Continuing Certification program; and
1.00 credit toward the CME [and Self-Assessment requirements] of the American Board of Surgery’s Continuous Certification program

It is the CME activity provider's responsibility to submit participant completion information to ACCME for the purpose of granting MOC credit.